Evaluation of Potential SARS-CoV-2 Protease Inhibitors Using a Comprehensive Viral Kinetics Simulation Platform

The ongoing COVID-19 pandemic, which began in East Asia in late 2019 and spread worldwide during early 2020, had infected more than three million people (reported cases), claimed in excess of 200,000 human lives, and wreaked immeasurable economic havoc as of late April 2020 [1]. The global scientific community is making a concerted effort to identify and develop safe and effective vaccines and anti-viral compounds for this new pathogen. Preliminary research studies that quickly identify a field of highly attractive inhibitor candidates can direct the course of further in-depth experimental work, thus minimizing the cost and total development time for ultimately successful drugs. Here, we present a novel approach that incorporates the results from molecular-scale protein-ligand in-vitro kinetic studies (i.e., using surface plasmon resonance, biolayer interferometry, and enzyme-linked immunosorbent assay techniques) into a bulk-scale within-host (target cell-limited) model of acute viral infection dynamics. The base (unperturbed) ordinary differential equation model for levels of virions, uninfected and infected cells (including viral replication and innate and acquired immune response) is first fit to a pooled (average) clinical SARS-CoV-2 viral load versus days post onset of symptoms profile to determine the model parameter set in the absence of an inhibitor. The rate constant for infection of uninfected target cells for cases in which an inhibitor (anti-viral compound) is administered at the onset of symptoms is adjusted using the molecular-scale reaction mechanism (i.e., competitive, non-competitive, or mixed enzyme inhibition kinetics) and cellular and virion structural features. The combined model is used to simulate the effects of several identified main and 3C-like protease (Mpro and 3CLpro) inhibitors [2] on temporal profiles of viral load and uninfected and infected cell levels. Inhibitors are ranked in terms of relative recovery time and fraction of healthy cell loss.

1. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU).

2. E Gordon et. al., A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing, bioRxiv preprint doi: https://doi.org/10.1101/2020.03.22.002386.